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Abstract

Microbiome studies have contributed to many fields, such as healthcare and medicine; however, these studies are relatively limited in forensics. Microbiome analyses can provide information, such as geolocation and ancestry information, when short tandem repeat (STR) profiling fails. In this study, methods for DNA extraction and sampling from the skin and saliva were optimized for the construction of a Korean Forensic Microbiome Database (KFMD). DNA yields were estimated using four DNA extraction kits, including two automated kits (Maxwell® FSC DNA IQ™ Casework Kit and PrepFiler™ Forensic DNA Extraction Kit, updated) and two manual kits (QIAamp DNA Mini Kit and QIAamp DNA Micro Kit) commonly used in forensic DNA profiling laboratories. Next-generation sequencing of the 16S rRNA V4 region was performed to analyze microbial communities in samples. The Bacterial Transport Swab with Liquid Media (NobleBio), two cotton swabs (PoongSung and Puritan), and nylon-flocked swabs (NobleBio and COPAN) were tested for DNA recovery. The PrepFiler and Maxwell kits showed the highest yields of 3.884 ng/μL and 23.767 ng/μL from the scalp and saliva, respectively. With respect to DNA recovery, nylon-flocked swabs performed better than cotton swabs. The relative abundances of taxa sorted by DNA extraction kits were similar contributions; however, with significant differences in community composition between scalp and saliva samples. Lawsonella and Veillonella were the most abundant genera in the two sample types. Thus, the Maxwell® FSC DNA IQ™ Casework Kit and nylon-flocked swab (NobleBio) were optimal for DNA extraction and collection in microbiome analyses.

Details

Title
Optimization of DNA extraction and sampling methods for successful forensic microbiome analyses of the skin and saliva
Author
Yu, Kyeong-Min 1 ; Lee, A-mi 1 ; Cho, Hye-Seon 1 ; Lee, Ji-woo 1 ; Lim, Si-Keun 1   VIAFID ORCID Logo 

 Sungkyunkwan University, Department of Forensic Sciences, Suwon, Republic of Korea (GRID:grid.264381.a) (ISNI:0000 0001 2181 989X) 
Pages
63-77
Publication year
2023
Publication date
Jan 2023
Publisher
Springer Nature B.V.
ISSN
09379827
e-ISSN
14371596
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2760983935
Copyright
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.